Eddy Covariance Methodology for Carbon, Water and Energy Exchanges

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Biosphere/Hydrosphere/Land–Atmosphere Interactions".

Deadline for manuscript submissions: closed (5 May 2023) | Viewed by 4952

Special Issue Editor


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Guest Editor
Joint Research Centre, European Commission, Ispra, Italy
Interests: GHG emissions; eddy covariance; boundary Layer meteorology

Special Issue Information

Dear Colleagues,

Twenty-five years ago, a few pioneering groups started measuring fluxes of carbon dioxide, water, and sensible heat between forests and atmosphere with a promising methodology: eddy covariance. Since then, the interest in field applications has increased steadily, leading to the development of several flux measurement networks around the globe and widening the spectrum of the studied ecosystems. With more time series heading to, sometimes even exceeding, the 20 year time horizon, we are now on the verge of measuring the breath of many ecosystems at time scales comparable to those of climate forcing. On the other side of the time spectrum (i.e., seconds to months), the meteorological and ecosystem modelling developments increased the spatial and time resolution of their domain, demanding the refined characterization of land-surface processes where turbulent fluxes are crucial. For these reasons, this Special Issue aims to collect updated views on eddy covariance applications including, but not limited to:

  • Exchanges from “hot spots” or underrepresented surfaces (e.g., Mediterranean, Tropics, urban or water surfaces);
  • Long-term ecosystem productivity and hydrology;
  • Integration with land-surface modelling or numerical weather prediction schemes. 

Dr. Nicola Arriga
Guest Editor

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Keywords

  • eddy covariance
  • productivity
  • hydrology
  • land surface
  • Numerical Weather Prediction
  • ecosystems

Published Papers (2 papers)

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Research

13 pages, 3943 KiB  
Article
Comparison of Atmospheric Turbulence Characteristics over Sea Surface and Land Surface before, during, and after Typhoons
by Xueyan Bi, Chao Lu, Chunxia Liu, Jian Huang, Honglong Yang, Zhongkuo Zhao and Qingtao Song
Atmosphere 2022, 13(11), 1827; https://doi.org/10.3390/atmos13111827 - 3 Nov 2022
Viewed by 1504
Abstract
The goal of the paper is to reveal discrepancies of turbulent variables over different surfaces (sea, island, land) based on the measurements taken on three towers during (including before and after) seven typhoon episodes from 2008 to 2018. The atmospheric stability, turbulent spectrum, [...] Read more.
The goal of the paper is to reveal discrepancies of turbulent variables over different surfaces (sea, island, land) based on the measurements taken on three towers during (including before and after) seven typhoon episodes from 2008 to 2018. The atmospheric stability, turbulent spectrum, friction velocity, turbulent kinetic energy, dissipative heating, and gust factor are examined. The similar turbulent characteristics over sea and on the island reinforce the previous conclusion that the turbulent measurements on the island mainly represent the sea surface. The turbulent characteristics over sea and on land are very different due to the different underlying surface roughness. The unstable (stable) condition dominates on the sea (land) surface. Turbulent spectra both over sea and on land follow the canonical Kolmogorov’s power law with the −5/3 slope. The cospectra on land are more peaked than those over sea. All of the friction velocity, turbulent kinetic energy, and dissipative heating increase with increasing 10 m wind speed, and those on land are much larger than those over sea. The distributions of gust factors widen and shift to higher on land than those over sea. The distributions of gust factors at heights of 10 m and 40 m are biased to higher values than those at heights of 160 m and 320 m on land. Full article
(This article belongs to the Special Issue Eddy Covariance Methodology for Carbon, Water and Energy Exchanges)
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20 pages, 4513 KiB  
Article
Intra-Seasonal and Intra-Annual Variation of the Latent Heat Flux Transfer Coefficient for a Freshwater Lake
by Gabriella Lükő, Péter Torma and Tamás Weidinger
Atmosphere 2022, 13(2), 352; https://doi.org/10.3390/atmos13020352 - 19 Feb 2022
Cited by 4 | Viewed by 2182
Abstract
In the case of lakes, evaporation is one of the most significant losses of water and energy. Based on high-frequency eddy-covariance (EC) measurements between May and September of 2019, the offshore heat and water vapor exchanges are evaluated for the large (~600 km [...] Read more.
In the case of lakes, evaporation is one of the most significant losses of water and energy. Based on high-frequency eddy-covariance (EC) measurements between May and September of 2019, the offshore heat and water vapor exchanges are evaluated for the large (~600 km2) but shallow (~3.2 m deep) Lake Balaton (Transdanubian region, Hungary). The role of local driving forces of evaporation in different time scales (from 20 min to one month) is explored, such as water surface and air temperatures, humidity, atmospheric stability, net radiation, and energy budget components. EC-derived water vapor roughness lengths and transfer coefficients (Cq) show an apparent intra-seasonal variation. Different energy balance-based evaporation estimation methods (such as the Priestley-Taylor and the Penman-Monteith) confirm this observation. Furthermore, this has suggested the existence of an intra-annual variation in these parameters. This hypothesis is verified using ten years of water balance measurements, from which, as a first step, evaporation rates and, second, transfer coefficients are derived on a monthly scale. Cq is highly reduced in winter months (~1 × 10−3) compared to summer months (~2.5 × 10−3) and strongly correlated with net radiation. The application of time-varying Cq significantly increases the accuracy of evaporation estimation when the Monin-Obukhov similarity theory-based aerodynamic method is applied. The determination coefficient increases to 0.84 compared to 0.52 when a constant Cq is employed. Full article
(This article belongs to the Special Issue Eddy Covariance Methodology for Carbon, Water and Energy Exchanges)
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